CN105593860B - For determining the device and patient health condition determiner of composite score distribution - Google Patents
For determining the device and patient health condition determiner of composite score distribution Download PDFInfo
- Publication number
- CN105593860B CN105593860B CN201480054182.9A CN201480054182A CN105593860B CN 105593860 B CN105593860 B CN 105593860B CN 201480054182 A CN201480054182 A CN 201480054182A CN 105593860 B CN105593860 B CN 105593860B
- Authority
- CN
- China
- Prior art keywords
- scoring
- distribution
- composite score
- branch mailbox
- vital sign
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000009826 distribution Methods 0.000 title claims abstract description 105
- 239000002131 composite material Substances 0.000 title claims abstract description 86
- 230000036541 health Effects 0.000 title claims description 83
- 238000005259 measurement Methods 0.000 claims abstract description 23
- 230000003862 health status Effects 0.000 claims abstract description 13
- 238000009528 vital sign measurement Methods 0.000 claims abstract description 13
- 239000004615 ingredient Substances 0.000 claims abstract description 5
- 238000003860 storage Methods 0.000 claims description 11
- 150000001875 compounds Chemical class 0.000 claims description 7
- 230000002045 lasting effect Effects 0.000 claims 2
- 238000000034 method Methods 0.000 abstract description 12
- 238000012986 modification Methods 0.000 description 18
- 230000004048 modification Effects 0.000 description 18
- 238000013459 approach Methods 0.000 description 8
- 230000036387 respiratory rate Effects 0.000 description 7
- 238000012544 monitoring process Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 230000035488 systolic blood pressure Effects 0.000 description 4
- 238000009825 accumulation Methods 0.000 description 3
- 230000009471 action Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 230000001186 cumulative effect Effects 0.000 description 3
- 238000013507 mapping Methods 0.000 description 3
- 230000036772 blood pressure Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 238000012806 monitoring device Methods 0.000 description 2
- 230000001537 neural effect Effects 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- TVZRAEYQIKYCPH-UHFFFAOYSA-N 3-(trimethylsilyl)propane-1-sulfonic acid Chemical compound C[Si](C)(C)CCCS(O)(=O)=O TVZRAEYQIKYCPH-UHFFFAOYSA-N 0.000 description 1
- 208000030090 Acute Disease Diseases 0.000 description 1
- 241000208340 Araliaceae Species 0.000 description 1
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 1
- 235000003140 Panax quinquefolius Nutrition 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 230000036760 body temperature Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000005315 distribution function Methods 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 230000008451 emotion Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 235000008434 ginseng Nutrition 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 210000005036 nerve Anatomy 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 210000000056 organ Anatomy 0.000 description 1
- 229910052760 oxygen Inorganic materials 0.000 description 1
- 239000001301 oxygen Substances 0.000 description 1
- 230000029058 respiratory gaseous exchange Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 230000001932 seasonal effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 208000024891 symptom Diseases 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- Biomedical Technology (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Pathology (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Abstract
A kind of method includes using at least first predetermined branch mailbox and the second predetermined branch mailbox, and next life ingredient safety pin is at least first set of vital sign measurement and at least the first histogram of second set and the second histogram.Each of described first set and the second set of the vital sign measurement include at least two measurement results acquired at different time, and Dai-ichi Mutual Life Insurance sign and the second vital sign are different vital sign.The method also includes generating the first scoring distribution for the Dai-ichi Mutual Life Insurance sign by the way that each branch mailbox in the described first predetermined branch mailbox is mapped to corresponding predetermined scoring.The method also includes generating the second scoring distribution for second vital sign by the way that each branch mailbox in the described second predetermined branch mailbox is mapped to corresponding predetermined scoring.The method also includes being distributed to generate for the composite score of the Dai-ichi Mutual Life Insurance sign and second vital sign based on the first scoring distribution and the second scoring distribution, the health status of the composite score distribution instruction patient.
Description
Technical field
The health status of monitoring patient is hereafter related generally to, and more particularly to multiple by patient health state
It closes scoring distribution and/or determines the health status of patient based on its representative composite scoring.
Background technique
Such as the patient health condition grading of early warning (body temperature) and/or other scorings are used in patient-monitoring, with
Medical supplier is helped to assess the seriousness and its progression risk of status of patient.Such scoring is typically based on to vital sign
Set single observation.For example, within the hospital, nurse is on duty every time will run (example many times from ward to ward
Such as, in its beginning on duty and centre), and the vital sign of acquisition respiratory rate, heart rate, systolic pressure, temperature etc., and lead to
It crosses observation and the neural status of each patient is assessed in inquiry.
The information interrogated from a wheel has been used for creating early warning scoring.It is pre- that Fig. 1 shows prior art early stage
The example of alert scoring.Table or matrix form are taken in early warning scoring, wherein each column expression indicates in header cell
Specific score value, every row indicate the health parameter (for example, vital sign) indicated in header cell, and the unit in body includes
Score value is mapped to the standard of health parameter.In the concrete example, respiratory rate 17, heart rate 60, systolic pressure are
90, temperature is 37 and shows the scoring of the patient with 4 (or 1+0+1+0+2) of " pain " symptom.
Regrettably, which provides the narrow time snapshot (single point in time) of patient health state.In addition, the approach does not have
Have and make full use of all available informations, such as, passes through (for example) automatic measurement health parameter continuously or periodically
Bed by electronic equipment or the monitor health status information that utilizes higher frequency to obtain.In addition, from ward to ward and from
Patient to patient runs, and manually acquires health parameter or the automatic collection of health parameter is called to consume medical treatment
The time of healthcare provider can be used for providing patient care in other cases.
" the Early warning scores derived from Statistical of publication L.Tarassenko etc.
distributions of vital signs",Resuscitation,Elsevier,IE,vol.82,no.8,11March
2011 (2011-03-11), the 1013-1018 pages describes a kind of life entity based on the admission patients in risk
Early warning scoring (EWS) system of the statistics property of sign.It is acquired using bedside monitor from 863 acute disease in-patients
The big data set of vital sign data be used to study the statistics property of four kinds of major vital signs.For in four variables
Each drafting normalization histogram and cumulative distribution function.Using sum total database to the warning system based on percentile into
Row modeling.
Various aspects described herein solves the above problem and other problems.
Summary of the invention
A kind of approach is described below, wherein the set of multiple and different health parameter measurement results is used for determining
The distribution of patient health state composite score and/or the single composite score of representativeness based on it.In an example, described compound
Scoring distribution and/or representative single composite score are convenient for the evaluation to patient health state.
In an aspect, a kind of according to claim 1 comment for determining that patient health state is compound is provided
The method of distribution.It includes using at least first predetermined branch mailbox and the second predetermined branch mailbox, and next life, ingredient safety pin was to vital sign
At least first set of measurement result and at least the first histogram of second set and the second histogram.The life sign measurement
As a result each of described first set and the second set include at least two measurement knots acquired at different time
Fruit, and Dai-ichi Mutual Life Insurance sign and the second vital sign are different vital sign.The method also includes by by described the
Each branch mailbox in one predetermined branch mailbox is mapped to corresponding predetermined scoring and comments to generate for the first of the Dai-ichi Mutual Life Insurance sign
Distribution.The method also includes by by each branch mailbox in the described second predetermined branch mailbox be mapped to it is corresponding it is predetermined scoring come
Generate the second scoring distribution for second vital sign.The method also includes based on the first scoring distribution and institute
The second scoring distribution is stated to be distributed to generate for the composite score of the Dai-ichi Mutual Life Insurance sign and second vital sign, it is described
The health status of composite score distribution instruction patient.
In another aspect, a kind of patient health condition determiner includes at least one histogram generator, it is described at least
One histogram generator uses at least first predetermined branch mailbox and the second predetermined branch mailbox, and next life, ingredient safety pin was to life sign measurement
As a result at least the first histogram and the second histogram of at least first set and second set.The vital sign measurement
The first set and each of the second set include at least two measurement results acquired at different time, and
And Dai-ichi Mutual Life Insurance sign and the second vital sign are different vital sign.The patient health condition determiner further includes individual
Score distribution determiner, and the individual scoring distribution determiner is by the way that each branch mailbox in the described first predetermined branch mailbox to be mapped to
Corresponding predetermined scoring is distributed to determine to score for the first of the Dai-ichi Mutual Life Insurance sign, and by making a reservation for described second
Each branch mailbox in branch mailbox is mapped to corresponding predetermined scoring to determine the second scoring distribution for second vital sign.
The patient health condition determiner further includes composite score distribution determiner, and the composite score distribution determiner is based on described
First scoring distribution and the second scoring distribution are determined for the Dai-ichi Mutual Life Insurance sign and second vital sign
Composite score distribution, wherein the health status of the composite score distribution instruction patient.
In another aspect, a kind of computer readable storage medium is encoded with computer-readable instruction, the computer
Readable instruction enables the processor when being executed by a processor: using at least first predetermined branch mailbox and the second predetermined branch mailbox, next life
Ingredient safety pin is at least first set of vital sign measurement and at least the first histogram of second set and the second histogram
Figure.Each of described first and second set of the vital sign measurement includes acquiring at least at different time
Two measurement results.Dai-ichi Mutual Life Insurance sign and the second vital sign are different vital sign.The computer-readable instruction is worked as
Also enable the processor corresponding pre- by the way that each branch mailbox in the described first predetermined branch mailbox to be mapped to when being run by processor
Accepted opinion point is distributed to generate to score for the first of the Dai-ichi Mutual Life Insurance sign.The computer-readable instruction is worked as to be transported by processor
Also enable the processor by the way that each branch mailbox in the described second predetermined branch mailbox is mapped to corresponding predetermined scoring next life when row
At the second scoring distribution for second vital sign.The computer-readable instruction also enables institute when being executed by a processor
Processor is stated based on the first scoring distribution and the second scoring distribution to generate for the Dai-ichi Mutual Life Insurance sign and institute
State the composite score distribution of the second vital sign.The health status of the composite score distribution instruction patient.
Detailed description of the invention
The present invention can take the form of various parts and each component layout, and can take various steps and each step
The form of arrangement.Attached drawing is not necessarily to be construed as limitation of the present invention merely to preferred illustrated embodiment.
Fig. 1 shows prior art early warning scoring.
Fig. 2 schematically illustrates example patient health condition determiner comprising with object and one or more healthy shapes
The composite score distribution determiner that state parameter sensors combine.
Fig. 3 illustrates the physiological measurement for health parameter acquired in specific time predefined window
The example of set.
Fig. 4 illustrates the example histogram generated for the set of the measurement result of Fig. 3.
Fig. 5 illustrates the example individual scoring distribution based on the histogram for multiple and different health parameters.
Fig. 6 schematically illustrates the example of composite score distribution determiner.
Fig. 7 schematically illustrates the example of composite score distribution.
What Fig. 8 schematically illustrated Fig. 2 includes the determining modification of representative composite scoring.
Fig. 9 illustrates example accumulation composite score histogram.
Figure 10 schematically illustrates the modification including filter of Fig. 2 or Fig. 3.
Figure 11 schematically illustrates the modification including tracker of Fig. 2, Fig. 3 or Figure 10.
Figure 12 schematically illustrates the modification including evaluator of Fig. 2, Fig. 3, Figure 10 or Figure 11.
Figure 13 illustrates another sample method of the example according to this paper.
Specific embodiment
It is described below and determines patient health degree for the set of the patient health state parameter according to the measurement that can be scored
Amount-composite score distribution approach.Optionally, based on its single composite score of representativeness.Additionally or alternately, the shape
Condition state measurement otherwise can be used to assess the uncertainty of patient's states, patient's states with the development of time with
And other features.It will can be used to be exported the algorithm of single every observation scoring by single observation, be used for by each single observation/single
Every observation scoring exports the algorithm of single composite score and/or other algorithms are used together with the approach.
Fig. 2 schematically illustrates the model combined with object 202 (for example, human or animal) and N number of state parameter sensor 204
Example patient health condition determiner 200, the state parameter sensor includes health parameter sensor 2041..., it is strong
Health state parameter sensor 204N(wherein, N is greater than the integer equal to 1).
In an example, at least one of health parameter sensor 204 sense health status information, such as but
It is not limited to, one or more of systolic pressure, respiratory rate, heart rate or temperature.For example, health parameter sensor 204 is strong
Health state parameter sensor may include (non-intrusion type or intrusive) blood pressure monitor etc..Health parameter sensor
204 frequencies sensed at which depend on sensed specific health parameter.
Optionally, the health parameter sensor of health parameter sensor 204 includes camera (static and/or view
Frequently), recorder etc., the health parameter sensor sensing object movement, behavior, emotion etc. and/or language, sound etc..
Such information can be evaluated by computer and/or people, to determine the neural state of object, such as, they whether be
It is vigilance, unresponsive, speak, in pain it is medium.People, which is also able to carry out, to be observed and observed result is input to healthy shape
In state parameter sensors 204.
Health parameter sensor 204 generates the electric signal of the health parameter of instruction sensing.The signal can
It is analog and/or digital signal.Digital signal can be converted analog signals into.The signal is being passed to health status ginseng
It, can be by health parameter sensor 204 and/or health parameter sensor 204 when counting the equipment outside sensor 204
External equipment (for example, analog-digital converter) executes such conversion.
The analog and/or digital signal can be stored in N number of health parameter sensor 204 (such as to show
) computer storage in, in the computer storage of central monitoring station, in the computer storage of data repository
(for example, object electron medicine record etc. in), in the computer storage of patient health condition determiner 200 and/or
In other computer storages.Such memory can store all signals, only predetermined specific (for example, nearest)
Signal etc. in time window.
Health parameter sensor 204 can be the part of the identical equipment of such as multi-parameter monitoring device.Alternatively, healthy
At least two in state parameter sensor 204 be the part of identical equipment, and in health parameter sensor 204 extremely
Few one be distinct device part.Alternatively, each of two at least in health parameter sensor 204 are
The part of distinct device.The example of such equipment includes but is not limited to blood pressure monitor, heart rate monitor, thermometer, breathing
Rate monitor, oxygen saturation monitor etc..
Patient health condition determiner 200 includes multiple histogram generators 206, including histogram generator
2061..., histogram generator 206N.In modification, histogram generator is implemented by single histogram generator 206
206.In modification, implement histogram generator 206 by multivariable histogram generator, generates and be directed to multiple sensors
Probability function.In the example of diagram, make in each of health parameter sensor 204 and histogram generator 206
Corresponding one it is associated so that health parameter sensor 2041With histogram generator 2061Communication ... ..., health
State parameter sensor 204NWith histogram generator 206NCommunication.
Such communication includes conveying signal between them.Pass through example, histogram generator 2061It can be for institute
The sometime block of the sensing signal of storage is to health parameter sensor 2041Request signal is transmitted, and in response,
From health parameter sensor 204NObtain signal.Pass through another example, histogram generator 2061Access health parameter
Sensor 2041Memory, and obtain the sometime block of the sensing signal of storage.Histograms different for two generate
The time block can be identical or different for device 206.
Each acquisition in histogram generator 206 corresponds to the sensing signal of predetermined time window.For example, histogram is raw
Grow up to be a useful person 2061It obtains and is based on time window 2081Sensing signal ... ..., histogram generator 206NIt obtains and is based on time window
208NSensing signal.As discussed above, health parameter sensor 204 can be sensed at different frequency and (be adopted
Collection, sampling etc.).So, same or different quantity can be obtained from each of health parameter sensor 204
Sample.
Fig. 3 briefly is gone to, illustrates the example set for the sample of time window.In Fig. 3, the expression of Y axis 302 is exhaled
Suction rate, x-axis 304 indicate the time, and curve 306 indicates the respiratory rate of the function as the time.Curve 306 be by using it is linear,
What batten and/or other approach connection individual specimen generated.As example, the sample can be small from the past one for range
When until current time time window.
Back to Fig. 2, histogram generator 206 generates histogram using signal obtained.In histogram generator 206
Each of using branch mailbox (bin) corresponding set.The branch mailbox of specific histogram can depend on the healthy shape being sensed
State parameter, and can be based on default, be defined by the user etc..In the example of diagram, histogram generator 2061Using
Branch mailbox 2101... ..., histogram generator 206NUsing branch mailbox 210N。
In the illustrated embodiment, each of histogram generator 206 generates histogram using the set of weight.?
In the example of diagram, histogram generator 2061Using weight 2121... ..., histogram generator 206NUsing weight 212N.Needle
The health parameter that be sensed can be depended on to the weight of specific histogram, and can be based on it is default, by with
What family defined etc..
In an example, the weight is weighted sample as the function of time, wherein for oldest acquisition
Sample have lowest weightings value, and for most recent acquisition sample have highest weight weight values.In this example, weight
It can change linearly or non-linearly between them.Other weighting functions have been also contemplated herein.In another example, weight
It can be entirely one (1) or be omitted.
Fig. 4 briefly is gone to, illustrates the example weighted histogram 402 of the sample based on Fig. 3.Y-axis 404 indicates sample value,
X-axis 406 indicates branch mailbox.For the example, oldest sample is weighted using zero, and is weighted as linearly increases
Add.In this example, branch mailbox is similar with those of respiratory rate is directed in Fig. 1.However, branch mailbox can be different.Histogram 402
Indicate the distribution of the sample based on branch mailbox.
Back to Fig. 2, individual scoring distribution determiner 214 is determined N number of straight based on scheduled scoring to branch mailbox mapping 216
Square to scheme distribution of scoring in each of (that is, histogram from N number of histogram generator 206), the scheduled scoring, which is arrived, to divide
Case mapping is provided to be mapped between each of branch mailbox of scoring and histogram, to define for each health parameter
Scoring/branch mailbox pair.Fig. 5 briefly is gone to, is shown for the scoring point of individual in each of multiple example health parameters
The example table or matrix of cloth.
In Fig. 5, every row 502 indicates different health parameters, and each column 504 indicates to be directed to health parameter value
Scoring.The first row in Fig. 5 indicates respiratory rate.Histogram 402 of the distribution of diagram from Fig. 4, wherein branch mailbox with figure
Similar mode is assigned to scoring in 1.For histogram 402, the 5% of sample is in the range of 9-14, the range pair
Should be in 1 scoring, 61% range in 15-20 of sample, the range corresponds to 0 scoring, and 35% sample is in
In the range of 21-29, the range corresponds to 1 scoring.
In Fig. 5, zero scoring indicates " normal " range.The scoring (for example, 1,2,3) increased from it is indicated " just
Often " the respiratory rate value outside range, either lower than (zero left side) or higher than (zero right side) " normal " range.It can utilize
Other mappings between other points-scoring systems, other branch mailbox, branch mailbox and scoring etc..Fig. 5 also show for heart rate, systolic pressure,
The scoring distribution of temperature and nerve.
Back to Fig. 2, composite score distribution determiner 218 determines that composite score is distributed based on individual scoring distribution.Energy
Enough use various approach.For example, in one non-limiting example, by calculating multiple scorings, then calculating for described more
A distribution of grading come determine composite score be distributed, wherein the multiple scoring each of correspond to health parameters observe
Subset (for example, the central value being derived from).
Other approach have been also contemplated herein.For example, describing another non-limiting example in conjunction with Fig. 6.It is non-limiting at this
In example, combination determiner 602 receives individual scoring distribution as input.Combine determiner 602 according to individual scoring distribution come
Determine all possible scoring combination.For example, combination determiner 602 has determined needle for five kinds of health parameters about Fig. 5
To all possible combinations of 15 entries in table.
Combination composite score determiner 604 is determined based on the various combination from combination determiner 602 for each group
The composite score of conjunction.For example, continuing the example in prior segment, there are the combinations that general comment is divided into zero-complete zero.For general comment
It is divided into one combination, there are six combinations.These combinations include in the health parameter one be one scoring,
With the scoring for being zero for every other health parameter.Other combinations are not discussed in detail for purposes of brevity,
But discussion based on this paper but it is obvious.
Individual scoring distribution of the combined probability determiner 606 based on the various combination from combination determiner 602 and input
To determine each combined probability.For example, continuing the example in first two sections, there are the combinations that general comment is divided into zero.For this
Combination, is distributed as 5%, 19%, 11%, 50% and 10%.Combined probability determiner 606 is by the determine the probability of the combination
For the product or (.05) (.19) (.11) (.50) (.10) of scoring distribution.
Composite score determine the probability device 608 determines the general of each composite score based on combination composite score and combined probability
Rate.For example, continuing the example of first three section, six there are overall score 1 are combined, and therefore six combined probabilities, for described
Each of six combinations, one.In this regard, determine the probability is a of six scoring combinations by composite score determine the probability device 608
The summation of body probability.
Composite score histogram determiner 610 based on for each composite score probability come determine composite score distribution or
Histogram.Fig. 7 briefly is gone to, illustrates example composite score distribution 706.In this example, y-axis 702 indicates that composite score is general
Rate, and x-axis 704 indicates composite score.Back to Fig. 2, patient health condition determiner 200 exports composite score distribution.?
In the example of diagram, composite score distribution is the summation of every health parameter scoring.In other instances, other can be utilized
Approach.
In the illustrated embodiment, composite score distribution is provided to one or more output equipments 220.One
Or multiple output devices 220 may include the display monitor, it is data repository, central monitoring station, smart phone, computer, all
Such as the DSS and/or other equipment of Clinical Decision Support Systems.In one non-limiting example, it is supervised via display
Visual organ visually shows the histogram similar to Fig. 7.Optionally, the list of action is visually presented together with the table.
In this case, the movement that the information indicating finger of visual display suggests (one or more) that each composite score is distributed.
Fig. 8 is gone to, the modification of Fig. 2 is illustrated.In this variant, patient health condition determiner 200 further includes representativeness
Score determiner 802.Representativeness scoring determiner 802 identifies representative single composite score, to indicate patient.In the example
In, other than composite score distribution and/or the list of proposal action, or as composite score distribution and/or proposal action
List it is alternative, single composite score is visually presented via one in output equipment 220.
In an example, the representative scoring can be based on accumulation composite score distribution.Fig. 9 shows accumulation
The non-limiting example of composite score distribution 906.In Fig. 9, Y-axis 902 indicates that cumulative probability, x-axis 904 indicate composite score.
In Fig. 9, for each scoring score value, the summation of the distribution for the value and much higher value is provided.The distribution can by with
In the representative scoring of export, for example, in an example, the representative scoring be with the cumulative probability higher than 50% most
High score value.
Composite score distribution, which can be used for establishing, deteriorates distribution of grading (opposite with single value), to indicate the shape of patient
State.Such distribution then can be used for exporting single representative value, but can also otherwise be used, such as with
Assess uncertainty, the development and other characteristics of patient's states at any time of patient's states.Patient health condition determiner 200
It can be medical supply and/or the part of general or specialized computer of such as patient monitoring devices.
Figure 10 illustrates the modification including filter 1000.In one non-limiting example, filter 1000 is based on pre-
Range of fixing time or time threshold are filtered the signal from health parameter sensor 204.For example, in a reality
In example, filter 1000 can be configured as filtering out the signal more early than target date D and/or predetermined time T.Specific date and/
Or the time can or can not change from health parameter to health parameter.In this example, filter 1000
Outside in patient health condition determiner 200.However, filter 1000 is at least partly patient in another modification
The part of health status determiner 200.
Figure 11 illustrates the modification including tracker 1100.In one non-limiting example, tracker 1100 is configured
To track scoring distribution and/or representative scoring for patient's current state at any time.In this example, at tracker 1100
In the outside of patient health condition determiner 200.However, tracker 1100 is at least partly that patient is strong in another modification
The part of health condition determiner 200.
Figure 12 illustrates the modification including evaluator 1200.In one non-limiting example, evaluator 1200 evaluates needle
History and current scoring distribution and/or representative scoring to the current state of patient.This may include to different time window
Between scoring distribution be compared (for example, the past one hour same time frame to yesterday;Past one hour to the past
24 hours;Past one hour to the previous hour before it;Etc.).It, can when that will pass by recently with being compared in the past
Equal weight is used to all observed results in the two time frame.In this example, evaluator 1200 is in patient health
The outside of condition determiner 200.
However, in another modification, evaluator 1200 be at least partly patient health condition determiner 200 part.
In modification, additionally it is possible to consider scoring distribution compared with PATIENT POPULATION.For example, scoring distribution can be with the phase in the time before
It is compared with the similar patient group stayed in season in identical mechanism.Allow to consider seasonal patient population structural reform in this way
Become.
Another modification includes the combination and/or other modifications of Figure 10,11 and/or 12.
Method of the invention can be implemented as the part of patient monitoring system, or can be embodied in and patient-monitoring
In the computer system of system engagement, a possibility that being also no lack of other certainly.
Figure 13 illustrates sample method.
It should be appreciated that the sequence of movement is not limiting.So, it is contemplated that other sequences.In addition, can
It to omit one or more movements, and/or may include one or more additional movements.
At 1302, at least two set of different physiological measurements are obtained, each set is included at least two
At least two measurement results acquired at different time.
At 1304, optionally, at least two set of weight are obtained, for two set of different physiological measurements
Each of, a set with weight.
At 1306, optionally using at least two set of weight, for at least two of different physiological measurements
Each of set generates health status distribution.
At 1308, all possible combined lists of scoring are determined based on the distribution of individual health condition grading.
At 1310, determined based on the combined list of all possible scorings for each combined composite score.
At 1312, it is directed to based on the distribution of individual health condition grading and all possible combined lists of scoring to determine
Each combined probability.
At 1314, it is directed to often based on for each combined composite score and for each combined probability to determine
The probability of a composite score.
At 1316, at least determine that health compound condition grading is distributed based on each combined probability is directed to.
At 1318, optionally, it is distributed based on the health compound condition grading to determine that representative composite scores.
At 1320, health compound condition grading is distributed and/or optional representative composite scoring provides output and sets
It is standby.
It can be by being encoded or being embedded in computer readable storage medium (that is, physical storage is non-transient with other
Medium) on computer-readable instruction come implement it is above act, the computer-readable instruction when by (one or more) it is micro-
When managing device operation, (one or more) processor is enabled to execute described movement.Additionally or alternately, described computer-readable
At least one of instruction is carried by signal, carrier wave and other state mediums.
The present invention is described by reference to preferred embodiment.Other people after reading and understanding the above detailed description can be real
Existing modifications and variations.The present invention is directed to be interpreted as including all such modifications and variations, as long as it falls into claims
Or within the scope of its equivalence.
Claims (15)
1. a kind of for determining the device of composite score distribution, described device includes processor and machine is executable to be referred to for storing
The memory of order, wherein the operation of the machine-executable instruction enables the processor:
Using at least first predetermined branch mailbox (406) and the second predetermined branch mailbox (406), Lai Shengcheng (1302) is directed to vital sign respectively
At least first set of measurement result (306) and at least the first histogram (402) of second set and the second histogram (402),
Wherein, each of the first set and the second set of the vital sign measurement (306) are included in
At least two measurement results acquired at different time, and Dai-ichi Mutual Life Insurance sign and the second vital sign are different life entity
Sign;
(1306) are generated for institute by the way that each branch mailbox in the described first predetermined branch mailbox is mapped to corresponding predetermined scoring
State the first scoring distribution of Dai-ichi Mutual Life Insurance sign;
It is generated by the way that each branch mailbox in the described second predetermined branch mailbox is mapped to corresponding predetermined scoring for described second
Second scoring distribution of vital sign;And
Generated based on the first scoring distribution and the second scoring distribution (1316) for the Dai-ichi Mutual Life Insurance sign and
The composite score of second vital sign is distributed (706,906).
2. the apparatus according to claim 1, wherein the operation of the machine-executable instruction also enables the processor:
The composite score is visually presented together with the list of the movement of the suggestion for each possible scoring to be distributed.
3. the apparatus according to claim 1, wherein generate at least first histogram and the second histogram includes being based on
Acquisition time is weighted (1304) to vital sign measurement.
4. the apparatus according to claim 1, wherein generating the composite score distribution includes:
(1308) all possible scoring combinations are identified based on the first scoring distribution and the second scoring distribution;
Determine (1310) for each combined composite score based on the scoring combination identified;
(1312) needle is determined based on the first scoring distribution and the second scoring distribution and the scoring combination identified
To each combined probability;
Determine that (1314) are directed to the probability of each composite score based on each combined probability is directed to;And
(1316) described composite score distribution is determined based on the probability for each composite score.
5. device according to claim 4, wherein determine that the probability for composite score includes to for described multiple
The individual probability for closing the scoring combination of scoring is summed.
6. device according to any one of claims 1 to 5, wherein the operation of the machine-executable instruction also enables
The processor:
It is distributed based on the composite score to determine that (1318) representative composite scores.
7. device according to any one of claims 1 to 5, wherein the operation of the machine-executable instruction also enables
The processor:
To at least first set and second set are filtered (1000) described in vital sign measurement, to remove in distance
The measurement result acquired before current time predetermined lasting time.
8. device according to any one of claims 1 to 5, wherein the operation of the machine-executable instruction also enables
The processor:
The composite score distribution is tracked at any time.
9. a kind of patient health condition determiner (200), comprising:
At least one histogram generator (206) generates difference using at least first predetermined branch mailbox and the second predetermined branch mailbox
At least the first histogram and the second histogram of at least first set and second set for vital sign measurement,
Wherein, when each of the first set and the second set of the vital sign measurement are included in different
Between at least two measurement results that acquire, and Dai-ichi Mutual Life Insurance sign and the second vital sign are different vital sign;
Individual scoring distribution determiner (214), it is corresponding by the way that each branch mailbox in the described first predetermined branch mailbox to be mapped to
Predetermined scoring is distributed to determine to score for the first of the Dai-ichi Mutual Life Insurance sign, and passing through will be in the described second predetermined branch mailbox
Each branch mailbox be mapped to it is corresponding it is predetermined scoring come determine for second vital sign second scoring distribution;And
Composite score distribution determiner (218) determines needle based on the first scoring distribution and the second scoring distribution
Composite score distribution to the Dai-ichi Mutual Life Insurance sign and second vital sign, wherein the composite score distribution instruction
The health status of patient.
10. patient health condition determiner according to claim 9, further includes:
At least one output equipment (220) is visually in together with the list of the movement of the suggestion for each possible scoring
The existing composite score distribution.
11. patient health condition determiner according to claim 9, wherein the composite score distribution determiner includes:
It combines determiner (602), is distributed based on the first scoring distribution and second scoring to identify and all may comment
Subassembly;
It combines composite score determiner (604), is combined based on the scoring identified and commented to determine for the compound of each combination
Point;
Combined probability determiner (606) is distributed and is identified based on the first scoring distribution and second scoring
Scoring combination is to determine for each combined probability;
Composite score determine the probability device (608) is determined based on the probability for each combination and compound is commented for each
The probability divided;And composite score histogram determiner (610), it is determined based on the probability for each composite score
The composite score distribution.
12. patient health condition determiner according to claim 9, wherein the composite score distribution determiner is to institute
It states the first scoring distribution and the second scoring distribution is summed to calculate the composite score distribution.
13. patient health condition determiner according to claim 9, further includes:
Representativeness scoring determiner (802) is distributed to determine that monodrome representative composite scores based on the composite score.
14. the patient health condition determiner according to any one of claim 9 to 13, further include in following at least
One:
Filter (1000), is filtered at least first set and second set described in vital sign measurement, with
It removes in the measurement result acquired before current time predetermined lasting time;
Tracker (1100) tracks the composite score distribution at any time;And
Evaluator (1200) is compared at least two composite scores distribution determined at least two different times.
15. a kind of computer readable storage medium for being encoded with computer-readable instruction, the computer-readable instruction when by
The processor operation season processor:
Using at least first predetermined branch mailbox and the second predetermined branch mailbox next life ingredient safety pin at least the of vital sign measurement
At least the first histogram and the second histogram of one set and second set,
Wherein, each of the first set and second set of the vital sign measurement are included at different time
At least two measurement results of acquisition, and Dai-ichi Mutual Life Insurance sign and the second vital sign are different vital sign;
It is generated by the way that each branch mailbox in the described first predetermined branch mailbox is mapped to corresponding predetermined scoring for described first
First scoring distribution of vital sign;
It is generated by the way that each branch mailbox in the described second predetermined branch mailbox is mapped to corresponding predetermined scoring for described second
Second scoring distribution of vital sign;And
It is directed to based on the first scoring distribution and the second scoring distribution next life into the Dai-ichi Mutual Life Insurance sign and described the
The composite score of two vital signs is distributed, wherein the health status of the composite score distribution instruction patient.
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201361884347P | 2013-09-30 | 2013-09-30 | |
US61/884,347 | 2013-09-30 | ||
PCT/IB2014/064509 WO2015044826A1 (en) | 2013-09-30 | 2014-09-15 | Patient health state compound score distribution and/or representative compound score based thereon |
Publications (2)
Publication Number | Publication Date |
---|---|
CN105593860A CN105593860A (en) | 2016-05-18 |
CN105593860B true CN105593860B (en) | 2019-08-06 |
Family
ID=51688372
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201480054182.9A Active CN105593860B (en) | 2013-09-30 | 2014-09-15 | For determining the device and patient health condition determiner of composite score distribution |
Country Status (6)
Country | Link |
---|---|
US (1) | US10037412B2 (en) |
EP (1) | EP3053066A1 (en) |
JP (1) | JP6534192B2 (en) |
CN (1) | CN105593860B (en) |
BR (1) | BR112016006577A2 (en) |
WO (1) | WO2015044826A1 (en) |
Families Citing this family (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11356554B2 (en) | 2016-02-25 | 2022-06-07 | Koninklijke Philips N.V. | Devices, system and methods for determining a priority level and/or conversation duration of a call |
CN109564782B (en) * | 2016-08-08 | 2024-03-08 | 皇家飞利浦有限公司 | Electronic clinical decision support equipment based on hospital demographics |
CN108768822B (en) * | 2018-04-11 | 2021-08-27 | 特素生物科技(天津)有限公司 | Body state self-diagnosis software and hardware system and method for establishing community |
WO2020203015A1 (en) * | 2019-04-02 | 2020-10-08 | 公立大学法人横浜市立大学 | Illness aggravation estimation system |
CN111035378B (en) * | 2020-03-17 | 2020-07-17 | 深圳市富源欣袋业有限公司 | Health data monitoring method based on travel bag and intelligent travel bag |
US11417429B2 (en) * | 2020-09-04 | 2022-08-16 | Centerline Holdings Llc | System and method for providing wellness recommendation |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102792336A (en) * | 2009-05-29 | 2012-11-21 | 电信教育集团-巴黎电信学校 | Method for quantifying the development of diseases involving changes in the volume of bodies, in particular tumours |
CN103038772A (en) * | 2010-03-15 | 2013-04-10 | 新加坡保健服务集团有限公司 | Method of predicting the survivability of a patient |
Family Cites Families (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2002095650A (en) | 2000-09-25 | 2002-04-02 | Teijin Ltd | Method of analyzing and treating clinical data and its system |
US20120296675A1 (en) * | 2006-02-13 | 2012-11-22 | Silverman David G | Method and System for Assessing, Quantifying, Coding & Communicating a Patient's Health and Perioperative Risk |
US8781566B2 (en) * | 2006-03-01 | 2014-07-15 | Angel Medical Systems, Inc. | System and methods for sliding-scale cardiac event detection |
US8768718B2 (en) * | 2006-12-27 | 2014-07-01 | Cardiac Pacemakers, Inc. | Between-patient comparisons for risk stratification of future heart failure decompensation |
US7629889B2 (en) * | 2006-12-27 | 2009-12-08 | Cardiac Pacemakers, Inc. | Within-patient algorithm to predict heart failure decompensation |
US20090093686A1 (en) * | 2007-10-08 | 2009-04-09 | Xiao Hu | Multi Automated Severity Scoring |
SG190397A1 (en) * | 2011-01-20 | 2013-06-28 | Nitto Denko Corp | Method and apparatus for deriving a health index for determining cardiovascular health |
GB201114406D0 (en) | 2011-08-22 | 2011-10-05 | Isis Innovation | Remote monitoring of vital signs |
-
2014
- 2014-09-15 CN CN201480054182.9A patent/CN105593860B/en active Active
- 2014-09-15 US US15/025,758 patent/US10037412B2/en active Active
- 2014-09-15 EP EP14781949.4A patent/EP3053066A1/en not_active Withdrawn
- 2014-09-15 WO PCT/IB2014/064509 patent/WO2015044826A1/en active Application Filing
- 2014-09-15 BR BR112016006577A patent/BR112016006577A2/en not_active Application Discontinuation
- 2014-09-15 JP JP2016545074A patent/JP6534192B2/en active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102792336A (en) * | 2009-05-29 | 2012-11-21 | 电信教育集团-巴黎电信学校 | Method for quantifying the development of diseases involving changes in the volume of bodies, in particular tumours |
CN103038772A (en) * | 2010-03-15 | 2013-04-10 | 新加坡保健服务集团有限公司 | Method of predicting the survivability of a patient |
Non-Patent Citations (1)
Title |
---|
Centile-based early warning scores derived from statistical distributions of vital signs;Lionel Tarassenko et.;《Resuscitation》;20111231;第82卷(第8期);第1013-1018页 |
Also Published As
Publication number | Publication date |
---|---|
US20160232323A1 (en) | 2016-08-11 |
JP6534192B2 (en) | 2019-06-26 |
WO2015044826A1 (en) | 2015-04-02 |
CN105593860A (en) | 2016-05-18 |
BR112016006577A2 (en) | 2017-08-01 |
US10037412B2 (en) | 2018-07-31 |
JP2016531712A (en) | 2016-10-13 |
EP3053066A1 (en) | 2016-08-10 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN105593860B (en) | For determining the device and patient health condition determiner of composite score distribution | |
CN102908130B (en) | Device for monitoring human health | |
Tjahjadi et al. | Noninvasive blood pressure classification based on photoplethysmography using k-nearest neighbors algorithm: a feasibility study | |
Welykholowa et al. | Multimodal photoplethysmography-based approaches for improved detection of hypertension | |
JPWO2019044619A1 (en) | Biometric information processing systems, biometric information processing methods, and computer programs | |
RU2657384C2 (en) | Method and system for noninvasive screening physiological parameters and pathology | |
WO2020123418A1 (en) | Patient monitoring system and method having severity prediction and visualization for a medical condition | |
US20220401037A1 (en) | Ml-based anomaly detection and descriptive root-cause analysis for biodata | |
CN109564586A (en) | System monitor and system monitoring method | |
CN116019429B (en) | Health monitoring method, device, equipment and storage medium based on physiological index | |
Milena et al. | Linear and non-linear heart rate variability indexes from heart-induced mechanical signals recorded with a skin-interfaced IMU | |
Tiwari et al. | Remote copd severity and exacerbation detection using heart rate and activity data measured from a wearable device | |
Warnecke et al. | Printed and flexible ECG electrodes attached to the steering wheel for continuous health monitoring during driving | |
Lueken et al. | Automated signal quality assessment of single-lead ECG recordings for early detection of silent atrial fibrillation | |
CN116098595B (en) | System and method for monitoring and preventing sudden cardiac death and sudden cerebral death | |
Georgieva-Tsaneva et al. | Cardiodiagnostics based on photoplethysmographic signals | |
JP6481335B2 (en) | Information processing system, information processing apparatus, information processing method, and information processing program | |
Durga | Intelligent support for cardiovascular diagnosis: The AI-CDSS approach | |
Lakudzode et al. | Review on human stress monitoring system using wearable sensors | |
Aghav et al. | Health track | |
Lang | A low-complexity model-free approach for real-time cardiac anomaly detection based on singular spectrum analysis and nonparametric control charts | |
Marwaha et al. | Optimal selection of threshold value ‘r’for refined multiscale entropy | |
Cvetković et al. | Monitoring patients with diabetes using wearable sensors: predicting glycaemias using ECG and respiration rate | |
Almeida et al. | Early warnings of heart rate deterioration | |
Wadhwani et al. | IOT based biomedical wireless sensor networks and machine learning algorithms for detection of diseased conditions |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |